Title | ||
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Search-evasion path planning for submarines using the Artificial Bee Colony algorithm |
Abstract | ||
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Submarine search-evasion path planning aims to acquire an evading route for a submarine so as to avoid the detection of hostile anti-submarine searchers such as helicopters, aircraft and surface ships. In this paper, we propose a numerical optimization model of search-evasion path planning for invading submarines. We use the Artificial Bee Colony (ABC) algorithm, which has been confirmed to be competitive compared to many other nature-inspired algorithms, to solve this numerical optimization problem. In this work, several search-evasion cases in the two-dimensional plane have been carefully studied, in which the anti-submarine vehicles are equipped with sensors with circular footprints that allow them to detect invading submarines within certain radii. An invading submarine is assumed to be able to acquire the real-time locations of all the anti-submarine searchers in the combat field. Our simulation results show the efficacy of our proposed dynamic route optimization model for the submarine search-evasion path planning mission. |
Year | DOI | Venue |
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2014 | 10.1109/CEC.2014.6900224 | IEEE Congress on Evolutionary Computation |
Keywords | Field | DocType |
submarines,artificial bee colony,hostile antisubmarine searcher detection avoidance,military vehicles,numerical optimization,two-dimensional plane,search-evasion path planning,helicopters,autonomous underwater vehicles,aircraft,numerical optimization model,submarine search-evasion path planning mission,circular footprints,antisubmarine vehicles,path planning,evading route,surface ships,dynamic route optimization model,abc algorithm,combat field,invading submarine detection,artificial bee colony algorithm,dynamic programming,real-time locations,mathematical model,tin,sensors,optimization | Motion planning,Artificial bee colony algorithm,Dynamic programming,Mathematical optimization,Computer science,Submarine,Operations research,Real-time computing,Optimization problem | Conference |
Citations | PageRank | References |
5 | 0.45 | 21 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Bai Li | 1 | 57 | 7.09 |
Raymond Chiong | 2 | 349 | 41.79 |
Ligang Gong | 3 | 5 | 0.45 |